PhD Position on Dynamical Models Learning for 3D Cell Imaging Data

Have you always wanted to work at the intersection of computer vision machine learning and biomedical imaging If the answer is yes please continue reading!

Join our team!

Live-cell 3D microscopy is revealing biology at a breathtaking spatio-temporal scale but todays object trackers still struggle with dense scenes extreme shape changes and hour-long recordings. Our new project brings together cutting-edge imaging at the Princess Mxima Imaging Center with state-of-the-art visual-tracking research in the Video & Image Sense Lab to solve this bottleneck.
We will develop an unsupervised or semi-supervised end-to-end cell tracker that links every pixel belonging to the same cell across space and time automatically adapts to complex deformations and recognises functional patterns such as T-cell serial killing in solid-tumour organoids. By delivering accurate long-term trajectories we open the door to quantitative cell-centric representations that can drive both fundamental discovery and next-generation immunotherapies.

What you will do

You will work at the intersection of computer vision machine learning and biomedical imaging to:

• Design methods that groups pixels into cells and links them over hours-long and non-trivial dynamics in 3D.
• Integrate Segment Anything / Segment Anything 2 priors and physics-informed constraints to boost robustness in crowded 3D scenes.
• Learn cell tracks into dynamics-aware representations that discover and detect salient cell behaviours (e.g. serial killing) directly from the learnt spatio-temporal graph.
• Benchmark the new tracker against academic baselines on BEHAV3D datasets and public cell-tracking challenges.
• Release code pretrained models and a user-friendly demo to the community.

Your work will be embedded in an interdisciplinary team of imaging scientists immunologists and AI researchers giving you access to world-class microscopes GPU clusters and rich annotated datasets.

Tasks and responsibilities:

• Conduct independent research leading to high-impact publications and open-source software.
• Collaborate with experimental partners to acquire curate and analyse large-scale 3D time-lapse data.
• Present findings at internal meetings international conferences and consortium workshops.
• Contribute up to 10% of your time to teaching (e.g. supervising MSc/BSc projects assisting practicals).
• Complete and defend a PhD thesis within four years.

Your profile

• MSc in Computer Science AI Applied Mathematics Biomedical Engineering or a related field.
• A strong background/knowledge in reinforcement learning causal learning or multimodal modals is a big plus.
• Solid background in deep learning graph neural networks or visual object tracking; experience with PyTorch or JAX is a plus.
• Experience with AI/HPC supercomputing and running software on scale.
• You are highly motivated independent and creative.
• Strong communication and collaboration (including to non-technical part of the team) presentation and writing skills and excellent command of English.
• Prior publications in relevant machine learning conferences or journals are advantageous.

Our offer

A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is 1 October 2025.This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.

The gross monthly salary based on 38 hours per week ranges between 3059 in the first year to 3881 in the last (scale P). This does not include 8% holiday allowance and 83% year-end allowance. The UFO profile PhD Candidate is applicable. A favourable tax agreement the 30% ruling may apply to non-Dutch applicants. The Collective Labour Agreement of Universities of the Netherlands is applicable.

Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:

• 232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January;
• multiple courses to follow from our Teaching and Learning Centre;
• a complete educational program for PhD students;
• multiple courses on topics such as leadership for academic staff;
• multiple courses on topics such as time management handling stress and an online learning platform with 100 different courses;
• 7 weeks birth leave (partner leave) with 100% salary;
• partly paid parental leave;
• the possibility to set up a workplace at home;
• a pension at ABP for which UvA pays two third part of the contribution;
• the possibility to follow courses to learn Dutch;
• help with housing for a studio or small apartment when youre moving from abroad.

Are you curious to read more about our extensive package of secondary employment benefits take a look here.

Where you will work

The Faculty of Science has a student body of around 8000 as well as 1800 members of staff working in education research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works be it elementary particles the birth of the universe or the functioning of the brain.

The mission of the Informatics Institute (IvI) is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence Computational Science and Systems and Network Engineering. Our research involves complex information systems at large with a focus on collaborative data driven computational and intelligent systems all with a strong interactive component.

The PhD studentship is jointly hosted by the Video & Image Sense Lab (VIS) at the University of Amsterdam and the Princess Mxima Center for Pediatric Oncology in Utrecht. You will spend most of your time at Amsterdam Science Parkhome to Europes largest academic GPU clusterwhile regularly communicating with part of the team in Princess Mxima Center responsible for performing experiments and datacollection on the state-of-the-art lattice light-sheet microscopes in Utrecht. Daily supervision will be provided by Dr. Gavves and Dr. Zadaianchuk (computer vision and ML/Representation Learning) and Dr. Rios (advanced imaging). You will join two vibrant international research groups that value open science diversity and a healthy worklife balance.

If you feel the profile fits you and you are interested in the job we look forward to receiving your application. You can apply online via the button. We accept applications until and including 31 August 2025. Applications should include the following information (all files besides your CV should be submitted in one single pdf file):

• A letter that motivates your choice for this position;
• Curriculum vitae including your list of publications if applicable (max 2 pages);
• A research statement on how to approach the PhD project. Solid and creative ideas will be greatly appreciated. (max 2 pages).
• A link to your Master thesis if online available else include an abstract.
• A complete record of Bachelor and Master courses (including grades and explanation of grading system);
• A list of projects or publications you have worked on with brief descriptions of your contributions max 1 page;
• The names and contact addresses of at least two academic references (please do not include any recommendation letters).

A knowledge security check can be part of the selection procedure (for details: national knowledge security guidelines).
Please use the CV field to upload your resume as a separate pdf document. Use the Cover Letter field to upload the other requested documents including the motivation letter as one single pdf file. Only complete applications received within the response period via the link below will be considered. The interviews for this position will be held in July and August.
Do you have any questions or do you require additional information Please contact:

• Stratis Gavves or Andrii Zadaianchuk